There are a finite number of possible inputs if the network is quantized. (And even if the network isn’t quantized, it just makes the possible input space much larger.) Especially if there’s been connection pruning for input nodes that don’t have a significant impact on the output.
Let’s say you have five inputs. For each possible input from node 1, you have a volume. Input is 3? Go grab volume 3. Node 2 relates to chapter; value is 10? Flip to chapter 10. Each chapter is a series of tables. Node 3 is for which table to look at, node 4 is row, node 5 is column. Voila, your five inputs have become a single output value.
Anything that is immutable and has a finite number of inputs and outputs can be represented by a lookup table.
That doesn’t sound anything like a neural network. Did you know that the chance of having a particular order of a deck of 52 cards shuffled 7 times is 8x10^67. What do you think the number of possible configurations is for a neural network of hundreds of millions of nodes?
I don’t understand how a network of weighted nodes could be represented by a lookup table.
There are a finite number of possible inputs if the network is quantized. (And even if the network isn’t quantized, it just makes the possible input space much larger.) Especially if there’s been connection pruning for input nodes that don’t have a significant impact on the output.
Let’s say you have five inputs. For each possible input from node 1, you have a volume. Input is 3? Go grab volume 3. Node 2 relates to chapter; value is 10? Flip to chapter 10. Each chapter is a series of tables. Node 3 is for which table to look at, node 4 is row, node 5 is column. Voila, your five inputs have become a single output value.
Anything that is immutable and has a finite number of inputs and outputs can be represented by a lookup table.
That doesn’t sound anything like a neural network. Did you know that the chance of having a particular order of a deck of 52 cards shuffled 7 times is 8x10^67. What do you think the number of possible configurations is for a neural network of hundreds of millions of nodes?
I never said it would be a reasonable size, just that it could be represented by a lookup table.